Mohammad Mahdi Dehshibi

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Mohammad Mahdi verified their affiliation via an institutional email.

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• Doctor of Philosophy
• Researcher at University Carlos III de Madrid

Regular light–dark cycles greatly affect organisms, and events like eclipses induce distinctive physiological and behavioural shifts. While well documented in animals, plant behaviour during eclipses remains largely unexplored. Here, we monitored multiple spruce trees to assess their individual and collective bioelectrical responses to a solar ecli...

Knowledge distillation (KD) remains challenging due to the opaque nature of the knowledge transfer process from a Teacher to a Student, making it difficult to address certain issues related to KD. To address this, we proposed UniCAM, a novel gradient-based visual explanation method, which effectively interprets the knowledge learned during KD. Our...

Spiking neural networks (SNNs) present the potential for ultra-low-power computation, especially when implemented on dedicated neuromorphic hardware. However, a significant challenge is the efficient conversion of continuous real-world data into the discrete spike trains required by SNNs. In this paper, we introduce Learning Adaptive Spike Threshol...

Chronic Low Back Pain (CLBP) afflicts millions globally, significantly impacting individuals’ well-being and imposing economic burdens on healthcare systems. Detecting protective behavior is essential for effective chronic pain management, as it can help prevent pain aggravation and disability. To reduce this burden, we could leverage sensor inform...

Knowledge distillation (KD) remains challenging due to the opaque nature of the knowledge transfer process from a Teacher to a Student, making it difficult to address certain issues related to KD. To address this, we proposed UniCAM, a novel gradient-based visual explanation method, which effectively interprets the knowledge learned during KD. Our...

The research poster introduces a new method for classifying chronic lower back pain (CLBP) using biosignals, specifically surface electromyography (sEMG) and inertial measurement unit (IMU) data. The study aims to improve CLBP detection and monitoring by introducing neuromorphic computing techniques to address the limitations of current methods, su...

Glaucoma, a leading cause of irreversible blindness worldwide, poses significant diagnostic challenges due to its reliance on subjective evaluation. Recent advances in computer vision and deep learning have demonstrated the potential for automated assessment. This paper provides a comprehensive survey of studies on AI-based glaucoma diagnosis using...

This paper presents the first application of spiking neural networks (SNNs) for the classification of chronic lower back pain (CLBP) using the EmoPain dataset. Our work has two main contributions. We introduce Spike Threshold Adaptive Learning (STAL), a trainable encoder that effectively converts continuous biosignals into spike trains. Additionall...

Magnetic fluids, commonly called ferrofluids, are excellent candidates for several important research fields, including computation, energy harvesting, biomedical applications, soft robotics, and exploration. Our study presents a groundbreaking discovery of significant phase correlations between two separate samples of ferrofluid, even when they ar...

Kombucha is a type of tea that is fermented using yeast and bacteria. During this process, a film made of cellulose is produced. This film has unique properties such as biodegradability, flexibility, shape conformability, and ability to self-grow as well as be produced across customized scales. In our previous studies, we demonstrated that Kombucha...

Chronic Low Back Pain (CLBP) afflicts millions globally, significantly impacting individuals' well-being and imposing economic burdens on healthcare systems. While artificial intelligence (AI) and deep learning offer promising avenues for analyzing pain-related behaviors to improve rehabilitation strategies, current models, including convolutional...

The energy efficiency of wireless sensor networks (WSNs) as a key feature of the Internet of Things (IoT) and fifth-generation (5G) mobile networks is determined by several key characteristics, such as hop count, user’s location, allocated power, and relay. Identifying important nodes, known as critical nodes, in IoT networks that involve a massive...

Glaucoma, a leading cause of irreversible blindness, necessitates early detection for accurate and timely intervention to prevent irreversible vision loss. In this study, we present a novel deep learning framework that leverages the diagnostic value of 3D Optical Coherence Tomography (OCT) imaging for automated glaucoma detection. In this framework...

Chronic Low Back Pain (CLBP) afflicts millions globally, significantly impacting individuals' well-being and imposing economic burdens on healthcare systems. While artificial intelligence (AI) and deep learning offer promising avenues for analyzing pain-related behaviors to improve rehabilitation strategies, current models, including convolutional...

Changes in body perception influence behavior and emotion and can be induced through multisensory feedback. Auditory feedback to one's actions can trigger such alterations; however, it is unclear which individual factors modulate these effects. We employ and evaluate SoniWeight Shoes, a wearable device based on literature for altering one's weight...

Regular light-dark cycles greatly affect organisms, and events like eclipses induce distinctive physiological and behavioural shifts. While well-documented in animals, plant behaviour during eclipses remains largely unexplored. Here we monitored multiple spruce trees to assess their individual and collective bioelectrical responses to a solar eclip...

To equip convolutional neural networks (CNNs) with explainability, it is essential to interpret how opaque models make specific decisions, understand what causes the errors, improve the architecture design, and identify unethical biases in the classifiers. This paper introduces ADVISE, a new explainability method that quantifies and leverages the r...

Body perception transformation technologies augment or alter our own body perception outside of our usual bodily experience. As emerging technologies, research on these technologies is limited to proofs-of-concept and lab studies. Consequently, their potential impact on the way we perceive and experience our bodies in everyday contexts is not yet w...

Body representations emerge through the integration of multisensory cues, facilitating interaction with the internal and external world. In this study, we empirically investigate the influence of integrating auditory cues with other multisensory and sensorimotor cues on perceptions of body size/weight. Participants (N=104) wore motion capture suits...

Glaucoma is the leading cause of irreversible blindness worldwide and poses significant diagnostic challenges due to its reliance on subjective evaluation. However, recent advances in computer vision and deep learning have demonstrated the potential for automated assessment. In this paper, we survey recent studies on AI-based glaucoma diagnosis usi...

Sensory-driven illusions, such as those produced by sounds in combination with tactile and/or proprioceptive cues, can significantly alter people's body perceptions. The footsteps illusion exemplifies this phenomenon. However, individual differences in the effects have been observed, which may be attributed to body ideals or symptomatology of eatin...

Nowadays, a significant part of our time is spent sharing multimodal data on social media sites such as Instagram, Facebook and Twitter. The particular way through which users present themselves to social media can provide useful insights into their behaviours, personalities, perspectives, motives and needs. This paper proposes to use multimodal da...

There is a growing body of studies on applying deep learning to biometrics analysis. Certain circumstances, however, could impair the objective measures and accuracy of the proposed biometric data analysis methods. For instance, people with chronic pain (CP) unconsciously adapt specific body movements to protect themselves from injury or additional...

The in situ measurement of the bioelectric potential in xilematic and floematic superior plants reveals valuable insights into the biological activity of these organisms, including their responses to lunar and solar cycles and collective behaviour. This paper reports on the “Cyberforest Experiment” conducted in the open-air Paneveggio forest in Val...

Smart wearables sense and process information from the user’s body and environment and report results of their analysis as electrical signals. Conventional electronic sensors and controllers are commonly, sometimes augmented by recent advances in soft electronics. Organic electronics and bioelectronics, especially with living substrates, offer a gr...

Oyster fungi Pleurotus djamor generate action potential like spikes of electrical potential. The trains of spikes might manifest propagation of growing mycelium in a substrate, transportation of nutrients and metabolites and communication processes in the mycelium network. The spiking activity of the mycelium networks is highly variable compared to...

Trees employ impulses of electrical activity to coordinate actions of their bodies and long-distance communication. There are indications that the vascular system might act as a network of pathways for traveling electrical impulses. A question arises about the correlation and interplay between the molecular (microscopic) level and the macroscopic o...

When English clubs and the game’s governing bodies and organizations turned off their Facebook, Twitter, and Instagram accounts from April 30 to May 1, 2021, the fight against online racism regained a new momentum. However, the Tokyo Olympics revealed new aspects of online bullying that athletes may face during major sporting events. Despite the sig...

Many samples are necessary to train a convolutional neural network (CNN) to achieve optimum performance while maintaining generalizability. Several studies, however, have indicated that not all input data in large datasets are informative for the model, and using them for training can degrade the model's performance and add uncertainty. Furthermore...

This work is dedicated to the review and perspective of the new direction that we call "Neuropunk revolution" resembling the cultural phenomenon of cyberpunk. This new phenomenon has its foundations in advances in neuromorphic technologies including memristive and bio-plausible simulations, BCI, and neurointerfaces as well as unconventional approac...

A reactive bacterial glove is a cotton glove colonised by Acetobacter aceti, an example of biofabrication of a living electronic sensing device. The bacterial colony, supported by a cellulose-based hydrogel, forms a several millimetres-thick living coating on the surface of the glove. This paper proposes a novel method for analysing the complex ele...

Electrical activity is used by plants in long term signalling and information transfer between the distant parts of the plant. Biopotential recordings from trees in a natural environment have been so far less discussed in scientific literature. Here we present our data about the open science experiment TRee-hUMAn iNterface (TRUMAN) located in Panev...

Electrical activity is used by plants in long term signalling and information transfer between the distant parts of the plant. Biopotential recordings from trees in a natural environment have been so far less discussed in scientific literature. Here we present our data about the open science experiment TRee-hUMAn iNterface (TRUMAN) located in Panev...

Early diagnosis of Alzheimer's disease and its prodromal stage, also known as mild cognitive impairment (MCI), is critical since some patients with progressive MCI will develop the disease. We propose a multi-stream deep convolutional neural network fed with patch-based imaging data to classify stable MCI and progressive MCI. First, we compare MRI...

To equip Convolutional Neural Networks (CNNs) with explainability, it is essential to interpret how opaque models take specific decisions, understand what causes the errors, improve the architecture design, and identify unethical biases in the classifiers. This paper introduces ADVISE, a new explainability method that quantifies and leverages the r...

Early diagnosis of Alzheimer's disease and its prodromal stage, also known as mild cognitive impairment (MCI), is critical since some patients with progressive MCI will develop the disease. We propose a multi-stream deep convolutional neural network fed with patch-based imaging data to classify stable MCI and progressive MCI. First, we compare MRI...

Fungal electronics is a family of living electronic devices made of mycelium bound composites or pure mycelium. Fungal electronic devices are capable of changing their impedance and generating spikes of electrical potential in response to external control parameters. Fungal electronics can be embedded into fungal materials and wearables or used as...

Fungal electronics is a family of living electronic devices made of mycelium bound composites or pure mycelium. Fungal electronic devices are capable of changing their impedance and generating spikes of electrical potential in response to external control parameters. Fungal electronics can be embedded into fungal materials and wearables or used as...

The re-emergence of mosquito-borne diseases (MBDs), which kill hundreds of thousands of people each year, has been attributed to increased human population, migration, and environmental changes. Convolutional neural networks (CNNs) have been used by several studies to recognise mosquitoes in images provided by projects such as Mosquito Alert to ass...

Monitoring the spread of disease-carrying mosquitoes is a first and necessary step to control severe diseases such as dengue, chikungunya, Zika or yellow fever. Previous citizen science projects have been able to obtain large image datasets with linked geo-tracking information. As the number of international collaborators grows, the manual annotati...

The re-emergence of mosquito-borne diseases (MBDs), which kill hundreds of thousands of people each year, has been attributed to increased human population, migration, and environmental changes. Convolutional neural networks (CNNs) have been used by several studies to recognise mosquitoes in images provided by projects such as Mosquito Alert to ass...

Fungi cells are capable of sensing extracellular cues through reception, transduction and response systems which allow them to communicate with their host and adapt to their environment. They display effective regulatory protein expressions which enhance and regulate their response and adaptation to a variety of triggers such as stress, hormones, l...

Monitoring the spread of disease-carrying mosquitoes is a first and necessary step to control severe diseases such as dengue, chikungunya, Zika or yellow fever. Previous citizen science projects have been able to obtain large image datasets with linked geo-tracking information. As the number of international collaborators grows, the manual annotati...

Oyster fungi Pleurotus djamor generate actin potential like spikes of electrical potential. The trains of spikes might manifest propagation of growing mycelium in a substrate, transportation of nutrients and metabolites and communication processes in the mycelium network. The spiking activity of the mycelium networks is highly variable compared to...

Smart wearables sense and process information from the user's body and environment and report results of their analysis as electrical signals. Conventional electronic sensors and controllers are commonly, sometimes augmented by recent advances in soft electronics. Organic electronics and bioelectronics, especially with living substrates, offer a gr...

Oyster fungi \emph{Pleurotus djamor} generate actin potential like spikes of electrical potential. The trains of spikes might manifest propagation of growing mycelium in a substrate, transportation of nutrients and metabolites and communication processes in the mycelium network. The spiking activity of the mycelium networks is highly variable compa...

For reconstructing CT images in the clinical setting, 'effective energy' is usually used instead of the total X-ray spectrum. This approximation causes an accuracy decline. We proposed to quantize the total X-ray spectrum into irregular intervals to preserve accuracy. A phantom consisting of the skull, rib bone, and lung tissues was irradiated with...

One of the significant problem in peer-to-peer databases is collision problem. These databases do not rely on a central leader that is a reason to increase scalability and fault tolerance. Utilizing these systems in high throughput computing cause more flexibility in computing system and meanwhile solve the problems in most of the computing systems...

Sharing multimodal information (typically images, videos or text) in Social Network Sites (SNS) occupies a relevant part of our time. The particular way how users expose themselves in SNS can provide useful information to infer human behaviors. This paper proposes to use multimodal data gathered from Instagram accounts to predict the perceived prot...

An excitable chemical medium --- Belousov-Zhabotinsky (BZ) reaction --- is proven to be a fruitful substrate for prototyping unconventional computing devices. These include image processors, logical circuits, and robot controllers. We study a BZ potential for characterising a geometry of street networks on a fragment of Tehran street map. The city...

Decanol droplets in a thin layer of sodium decanoate with sodium chloride exhibit bifurcation branching growth due to interplay between osmotic pressure, diffusion and surface tension. We aimed to evaluate if morphology of the branching droplets changes when the droplets are subject to electrical potential difference. We analysed graph-theoretic st...

Decanol droplets in a thin layer of sodium decanoate with sodium chloride exhibit bifurcation branching growth due to interplay between osmotic pressure, diffusion and surface tension. We aimed to evaluate if morphology of the branching droplets changes when the droplets are subject to electrical potential difference. We analysed graph-theoretic st...

A recent challenge in computer vision is exploring the cardinality of a relationship among multiple visual entities to answer questions like whether the subjects in a photograph have a kin relationship. This paper tackles kinship recognition from the aging viewpoint in which the system could find the parent of a child where the input image of the p...

Cellular nonlinear network (CNN) provides an infrastructure for Cellular Automata to have not only an initial state but an input which has a local memory in each cell with much more complexity. This property has many applications which we have investigated it in proposing a robust cryptology scheme. This scheme consists of a cryptography and stegan...

Computed Tomography (CT) imaging is one of the most influential diagnostic methods. In clinical reconstruction, an effective energy is used instead of total X-ray spectrum. This approximation causes an accuracy decline. To increase the contrast, single source or dual source dual energy CT can be used to reach optimal values of tissue differentiatio...

Unconventional computing is about breaking boundaries in thinking, acting and computing. Typical topics of this non-typical field include, but are not limited to physics of computation, non-classical logics, new complexity measures, novel hardware, mechanical, chemical and quantum computing. Unconventional computing encourages a new style of thinki...

In the field of image analysis, segmentation is one of the most important preprocessing steps. One way to achieve segmentation is the use of threshold selection, where each pixel that belongs to a determined class, based on the mutual visual characteristics, is labeled according to the selected threshold. In this work, a combination of two pioneer...

Numismatics sorts out historical aspects of money. Identification and classification of coins, as a part of their duties, need years of experience. This research aims at using the knowledge of numismatics for developing an image-based classification of ancient Sassanian dynasty coins. A straightforward method is to take coins observe and reverse-si...

Malware is defined as any type of malicious code that is the potent to harm a computer or a network. Modern malwares are accompanied with mutation characteristics, namely polymorphism and metamorphism. They let malwares to generate enormous number of variants. Rising number of metamorphic malwares entails hardship in analyzing them for signature ex...

To understand how the Persian language developed over time, we uncover the dynamics of the complexity of Persian orthography. We represent Persian words by L-systems and calculate complexity measures of these generative systems. The complexity measures include degrees of nonconstructability, generative complexity, and morphological richness; the me...

Ahstract-Face recognition has been a long standing problem in computer vision. Histograms of Oriented Gradients (HOGs) and Local Binary Patterns (LBPs) have proven to be an effective descriptor for object recognition in general and face recognition in particular. In this paper, we investigate a simple but powerful approach to make robust use of HOG...

Nowadays, no one can neglect the effect of smartphone applications in the daily life. Diversity of these applications are enormously increased, from entertainment to education. In the meantime, informative applications have their pros. In this research, producing a painter finder app has been taken into account. Finding adequate information about p...

Ahstract-This paper presents an automatic document processing system for the extraction of data which are illustrated in medical laboratory results printed on a paper. The final goal of the research is to make the collection of medical data automatic and to enable an efficient management and description of the information in a way that a patient or...

Conventionally, music sharing has been done through two ways: aural transmission and in the form of written documents which is normally called musical scores. As many of these paper based scores have not been published they are subj ected to be damaged. To preserve the music an application that has the capability of digitalizing these symbolic imag...

Complementary medicine emphasizes therapies which are claimed to improve quality of life, prevent disease, and address conditions that conventional medicine has limited success in curing. Iridology is an alternative medicine technique which examines patterns, colors, and other characteristics of the iris to determine information about a patient's s...

Lyndenmayer systems (L-systems) allow us to grow sophisticated patterns by applying just few simple rules. The L-systems are now universal tools for abstract representation of plant development. Can the L-systems be used to " grow " Persian words and sentences? Yes. We demonstrate this by introducing grammars and rules to generate 108 words of a Pe...

In this paper, a new method is proposed for finding the suitable forced landing sites for UAVs. This approach does not have any limitations of the previous few researches done in this area. For finding the suitable landing sites, we first segment the aerial images based on classification using both color and texture features. Classification is perf...

Ancient coins classification has attracted increasing attention for the benefits which it brings to numismatic community. However, high between-class similarity and, in the meantime, high within-class variability make the problem a particular challenge. This issue highlights the importance of extracting discriminative features for ancient coins cla...

An L-System is a parallel rewriting system and a type of formal grammar, which was introduced to be used in describing the behavior of plant cells, modeling the growth processes of plant development, the morphology of organisms, and generating self-similar fractals. The mentioned applications lie in the field of pattern formation. However, to the b...

Viseme (Visual Phoneme) classification and analysis in every language are among the most important preliminaries for conducting various multimedia researches such as talking head, lip reading, lip synchronization, and computer assisted pronunciation training applications. With respect to the fact that analyzing visemes is a language dependent proce...

The science of pattern formation deals with the visible, (statistically) orderly outcomes of self-organization and the common principles behind similar patterns in nature. Cell pattern formation has an important role in both artificial and natural development. Different methods have been utilized for pattern formation such as geometrical, Cellular...

Viseme (Visual Phoneme) clustering and analysis in every language is among the most important preliminaries for conducting various multimedia researches as talking head, lip reading, lip synchronization and computer assisted pronunciation training applications. With respect to the fact that clustering and analyzing visemes are language dependent pr...

In this paper, we propose a method for kernel–based object tracking in order to deal with partial occlusion. We use particle filter to estimate target position accurately. The incremental Bhattacharyya Dissimilarity (IBD) based stage is designed to consistently distinguish the particles located in the object region from the others placed in the bac...

Viseme (Visual Phoneme) clustering and analysis in every language is among the most important preliminaries for conducting various multimedia researches as talking head, lip reading, lip synchronization and computer assisted pronunciation training applications. With respect to the fact that clustering and analyzing visemes are language dependent pr...

In this paper, we propose a method for kernel-based object tracking in order to deal with partial occlusion. We use particle filter to estimate target position accurately. The incremental Bhattacharyya Dissimilarity (IBD) based stage is designed to consistently distinguish the particles located in the object region from the others placed in the bac...

There are numerous multimedia applications such as talking head, lip reading, lip synchronization, and computer assisted pronunciation training, which entices researchers to bring clustering and analyzing viseme into focus. With respect to the fact that clustering and analyzing visemes are language dependent process, we concentrated our research on...

Projection Functions have been widely used for facial feature extraction and optical/handwritten character recognition due to their simplicity and efficiency. Because these transformations are not one-to-one, they may result in mapping distinct points into one point, and consequently losing detailed information. Here, we solve this problem by defin...

Swarm intelligence algorithms have been extensively used in clustering based applications e.g. image segmentation which is one of the fundamental components in image analysis and pattern recognition domains. Particle swarm optimization is amongst swarm intelligence algorithms that performs based on population and random search. In this paper, a hyb...

Objective function or the constraints and consequently the optimal value of the problem can be changed during time in Dynamic optimization problems. There are several challenges in dynamic environments, so that algorithms designed for optimization in these environments would utilize several mechanisms in order to conquer the challenges. In this pap...

Immunocytochemistry (ICC) is a microscopic imaging technique that is used to assess the presence of a specific antigen in cells utilizing a specific antibody for allowing visualization and examination processes. Number of cells in an ICC image is considered as one of the most important indicators in the examination process. In this paper, an image...

Facial image analysis is one of the areas that have been received considerable attention in recent decades. In addition to areas such as face recognition, gender classification, emotion recognition, and age estimation, there are new applications that have not been studied yet. Family similarity recognition is a new trend that has been studied in th...

Although the capability and productivity of Cellular Automata (CA) entice researchers to bring them into focus, a few works have been reported on utilization of CA in the field of script generation. The focus of this research is not only on generating a type of ancient Persian script, so-called Ma'qeli, using block cellular automata with Margolus n...