Clifford Broni-Bediako

RIKEN | RIKEN AICS · AIP - Geoinformatics Unit

Multi-stage or multi-generator generative adversarial networks (GANs) have recently been demonstrated to be effective for speech enhancement. The existing multi-generator GANs for speech enhancement only use convolutional layers for synthesising clean speech signals. This reliance on convolution operation may result in masking the temporal dependen...

In recent years, the transformer achieved remarkable results in computer vision related tasks, matching, or even surpassing those of convolutional neural networks (CNN). However, unlike CNNs, those vision transformers lack strong inductive biases and, to achieve state-of-the-art results, rely on large architectures and extensive pre-training on ten...

Recently, pre-trained language models (PLMs) have become core components in a wide range of natural language processing applications. However, PLMs like BERT and RoBERTa are typically trained with a large amount of unlabeled text corpora which requires extremely high computational cost. Curriculum learning (CL) is a learning strategy for training a...

We introduce OpenEarthMap, a benchmark dataset, for global high-resolution land cover mapping. OpenEarthMap consists of 2.2 million segments of 5000 aerial and satellite images covering 97 regions from 44 countries across 6 continents, with manually annotated 8-class land cover labels at a 0.25--0.5m ground sampling distance. Semantic segmentation...

Recently, neural architecture search (NAS) has gained a lot of attention as a tool for constructing deep neural networks automatically. NAS methods have successfully found convolutional neural networks (CNNs) that exceed human expert-designed networks on image classification in computer vision. However, there are growing demands for semantic segmen...

Recently, the vision transformer (ViT) achieved remarkable results on computer vision-related tasks. However, ViT lacks the inductive biases present on CNNs, such as locality and translation equivariance. Overcoming this deficiency usually comes at high cost, with networks with hundreds of millions of parameters, trained over extensive training rou...

Discovering customer sentiment towards topics is an important task in sentiment analysis. Currently, most studies focus on using customers' reviews to understand user sentiments at the topic sentiment level. In this study, we develop a framework with a topic modelling technique and neural network to predict the topic sentiment polarity of customers...

Recently, the vision transformer (ViT) achieved remarkable results on computer vision related tasks. However, ViT lacks the inductive biases present on CNNs, such as locality and translation equivariance. Overcoming this deficiency usually comes at high cost, with networks with hundreds of millions of parameters, trained over extensive training rou...

Convolutional neural network (CNN) models for remote sensing (RS) scene classification are largely built on pretrained networks that are trained on the general-purpose ImageNet dataset in computer vision. The pretrained networks can easily be adapted for transfer learning in RS scene classification. However, the accuracy of transfer learning may de...

The renaissance of neural architecture search (NAS) has seen classical methods such as genetic algorithms (GA) and genetic programming (GP) being exploited for convolutional neural network (CNN) architectures. While recent work have achieved promising performance on visual perception tasks, the direct encoding scheme of both GA and GP has functiona...

The renaissance of neural architecture search (NAS) has seen classical methods such as genetic algorithms (GA) and genetic programming (GP) being exploited for convolutional neural network (CNN) architectures. While recent work have achieved promising performance on visual perception tasks, the direct encoding scheme of both GA and GP has functiona...

Arguably, El Niño-Southern Oscillation (ENSO) is the most influential climatological phenomenon that has been intensively researched during the past years. Currently, the scientific community knows much about the underlying processes of ENSO phenomenon, however, its predictability for longer horizons, which is very important for human society and t...

Arguably, El Niño-Southern Oscillation (ENSO) is the most influential climatological phenomenon that has been intensively researched during the past years. Currently, the scientific community knows much about the underlying processes of ENSO phenomenon, however, its predictability for longer horizons, which is very important for human society and t...