Arfan Jaffar's research while affiliated with University of Lahore and other places
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Publications (20)
Deep learning models, such as convolutional neural network (CNN), are popular now a day to solve various complex problems in medical and other fields, such as image classification, object detection, recommendation of images, processing of natural languages and video and image analysis. So, the idea of studying the architecture of CNNs has gotten a...
In computer vision, the convolutional neural network (CNN) is a very popular model used for emotion recognition. It has been successfully applied to detect various objects in digital images with remarkable accuracy. In this paper, we extracted learned features from a pre-trained CNN and evaluated different machine learning (ML) algorithms to perfor...
An intelligent sound-based early fault detection system has been proposed for vehicles using machine learning. The system is designed to detect faults in vehicles at an early stage by analyzing the sound emitted by the car. Early detection and correction of defects can improve the efficiency and life of the engine and other mechanical parts. The sy...
Batsmen are the backbone of any cricket team and their selection is very critical to the team's success. A good batsman not only scores run but also provides stability to the team's innings. The most important factor in selecting a batsman is their ability to score runs. It is a generally accepted notion that the future performance of a batsman can...
By June 2020, almost 9 million confirmed verified Covid-19 cases had been confirmed, with above 468 thousand deaths. Contact with tainted objects can transmit the viruses and touch your mouth, eyes, or nose to an infected person. Since how much corona diseases are spreading quickly, it is hard to test because of time and cost factors. For a long ti...
Lung cancer is the most common cause of cancer deaths around the globe. Early detection is crucial for successful treatment and increasing patient survival rates. Artificial intelligence techniques can play a significant role in the initial diagnosis of lung cancer. Various methods consisted of machine learning and deep learning methods are used to...
The most lethal and devastating form of cancer, breast cancer, is often first detected when a lump appears in the breast. The cause can be attributed to a typical proliferation of cells in the mammary glands. Early breast cancer detection improves survival. Breast cancer screening and early detection are commonly carried out using imaging technique...
Facial expression recognition (FER) is advancing human-computer interaction, especially, today, where facial masks are commonly worn due to the COVID-19 pandemic. Traditional unimodal techniques for facial expression recognition may be ineffective under these circumstances. To address this challenge, multimodal approaches that incorporate data from...
Breast common cancer kind of cancer that affects women globally. Around 30% of all new cases of cancer in women are anticipated to be breast cancer by 2022. This life-threatening disease is an incurable disease but controllable. Nevertheless, early diagnosis through routine inspection can boost recovery and survival chances. A computer-aided breast...
A critical issue is the acceptance of current modern smartphone technology by older people. Smartphones are inventions that presently offer significant advantages to help individuals. However, around the world, every older user wants to perform tasks that are more user-friendly, and near their personal preferences. Considering these factors, this r...
It has become easier to change the content of computerized photos as mixed media innovation has advanced. This is due to the wide availability of picture editing apps. If altered for a negative motive, created images can cause major social and legal problems. The detection of picture fraud requires the advancement of contemporary methods that can e...
Lung cancer is the most dangerous and death-causing disease indicated by the presence of pulmonary nodules in the lung. It is mostly caused by the instinctive growth of cells in the lung. Lung nodule detection has a significant role in detecting and screening lung cancer in Computed tomography (CT) scan images. Early detection plays an important ro...
Malignant melanoma is considered one of the deadliest skin diseases if ignored without treatment. The mortality rate caused by melanoma is more than two times that of other skin malignancy diseases. These facts encourage computer scientists to find automated methods to discover skin cancers. Nowadays, the analysis of skin images is widely used by a...
The convolutional neural network (CNN) has become a powerful tool in machine learning (ML) that is used to solve complex problems such as image recognition, natural language processing , and video analysis. Notably, the idea of exploring convolutional neural network architecture has gained substantial attention as well as popularity. This study foc...
According to the World Health Organization, 31% death rate in the World is because of cardiovascular diseases like heart arrhythmia and heart failure. Early diagnosis of heart problems may help in timely treatment of the patients and hence control death rate. Heart sounds are good signals of heart health if examined by an expert. Moreover, heart so...
Financial transaction is backbone of global market that
make it convenient for people to make their transaction easy.
People do transaction of money from everywhere using
banking system through e-banking or credit card system. That
is why banking sectors play a vital role in any country and
provide proper structure to any country and make their...
Purpose:
This paper proposes a novel splicing detection method utilizing a discriminative robust local binary pattern (DRLBP) with a support vector machine (SVM). Reliable detection of image splicing is of growing interest due to the extensive utilization of digital images as a communication medium and the availability of powerful image processing...
Citations
... Recently, FER methods of deep learning based on the convolutional neural network (CNN) have gained significant achievements [2,3]. Better results have been achieved for FER on the facial expression datasets CK+ [4], JAFFE [5], and so on taken under controlled conditions (laboratory, no complex background, etc.). ...
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... Additionally, we have conducted a comparative analysis of our method's accuracy with the results obtained by different authors who employed the VGG-16 and VGG-19 architectures on the MLF-W-FER dataset. Their reported accuracies were 55.6% [46] and 53.54% [47], respectively. By comparing these results, our method has exhibited superior accuracy. ...
... This direct observation during a roadside survey requires resources, as they can be costly and expensive [3]- [8]. And while using video cameras that allow indirect visibility, reducing the time-consuming pressure of hat use with direct view, human managers estimate the volume of information that can be processed. ...
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... Investigation through histopathology is a complex and time-consuming road to cancer diagnostic information. However, the strong professional experience of pathologists is crucial for the physical diagnosis of breast cancer which is time consuming, costly and misdiagnosis may also occur [2]. ...
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... Although there are other post-task evaluation methods, in this study satisfaction is gauged using the ASQ method. The ASQ is a relatively brief questionnaire that requires minimal time to complete, is simple to comprehend, and has a significant practical impact on participant considerations for usability studies [41][42][43][44][45][46][47][48]. ...
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... problem (1) can be solved using the theory of the multiplier symmetrical cone algorithm, for this we will give some concepts below. Let 1 : 1 × 1 → ℝ ∪ {+∞} be a function satisfying 1 ∈ ( ( 1 )). ...
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... Using Convolutional Neural Networks-based models, it will be possible to determine the pupil's centre [1] accurately. Artificial neural networks [2] are also improved the accuracy of medical diagnostic applications. Intelligent learning, enhanced network designs, and intelligent training methods are used, and CNN is thought to perform best in all vision-related applications. ...
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... This collection contains a total of 244,617 images of lungs, each one originating from a patient of a distinct age group [13,21,66,90,102]. Along with LIDC-IDRI database the some of the widely used databases are LC25000 [62], LUng Nodule Analysis (LUNA-16) [68,76], Lung Cancer Alliance (LCA) [110], Lungs Data Science Bowl Dataset (LDSBD-2017) [53], ELCAP Public Lung Image Database (ELCAP-PLID) [65], Iraq-Oncology Teaching Hospital-National Center for Cancer Diseases (ELCAP-PLID) [79]. ...
... With its ability to quickly and accurately analyze large amounts of sound data, it is helping doctors make better diagnoses, choose more effective treatments, and even predict patient outcomes. Random forest tree, Support Vector Machine (SVM), Artificial Neural network (ANN), and Dense Neural Network (DNN) is used in the detection of different diseases from medical sounds such as heart, lungs, and breath sounds [9][10][11][12][13][14]. An automatic method [15] has been developed to classify the breathing and snoring sound segments based on their energy, the zero-crossing frequency, and the format of the sound signals. ...
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