Mental stress persisting for long can cause severe health issues. There are various approaches available in the literature for investigating stress through speech utterances. The available procedure to obtain speech under ...
In the context of radar imaging antenna design, today, the major challenge is to achieve ultra-wide bandwidth encompassing operations at low gigahertz range (<2 GHz) with high gain which in turn provides better range ...
The development for a microwave imaging system, better resolution and good penetration depth are the most prominent constraints. To achieve these requirements, high gain antenna operating at low frequency ranges with ...
It is still a challenge for existing DNN based models to synergistically exploit the spatial, temporal, and especially spectral information of a crop present in multi-sensor time series (MSTS) remote sensing (RS) images ...
The biomedical image denoising method has developed into one of the most fascinating study fields today. Every day, lots of biomedical images are taken, and it is from these images that diseases have been diagnosed. To ...
Foliage penetrating (FOPEN) radar can see through foliage in clear weather as well as in presence of dust, smoke, rain and haze. Foliage is a complex clutter environment and target detection in this environment is a highly ...
The challenge of performing efficient and reliable crop classification with multisensor multitemporal (MSMT) images in mixed land cover scenarios i.e. presence of small land parcels (area < 20,000-meter square) of crops ...
Agriculture is the backbone of any community, as it provides the most necessity for human survival. Diseases on plants/crops in agriculture reduces the productivity, thus its presence and removal are mandatory for good ...
Synthetic aperture radar (SAR) data obtained at multiple frequencies and polarizations offers valuable complementary information for classifying mixed classes that exhibit similar backscattering response. Although deep ...
Drones have become increasingly popular in precision agriculture due to their ability to collect valuable data quickly and efficiently. One of the major aspects of precision agriculture is to estimate fraction crop cover ...
During floods, updated and accurate information on affected human settlements helps save lives and reduces time to rescue. Therefore, approaches that can provide reliable information during floods via the use of all-weather ...
In short-range microwave imaging, the collection of data in real environments for the purpose of developing techniques for target detection is very cumbersome. Simultaneously, to develop effective and efficient AI/ML-based ...
In this paper, we propose an efficient regression algorithm based on primal formulation of twin support vector machine. This is an efficient approach to solve the optimization problem leading to reduced computation time. ...
System testing is essential in any software development project to ensure that the final products meet the requirements. Creating comprehensive test cases for system testing from requirements is often challenging and ...
We introduce DebateBench, a novel dataset consisting of an extensive collection of transcripts and metadata from some of the world's most prestigious competitive debates. The dataset consists of British Parliamentary debates ...
This study examines the use of large language models (LLMs) by undergraduate and graduate students for programming assignments in advanced computing classes. Unlike existing research, which primarily focuses on introductory ...
The escalating volume of academic research, coupled with a shortage of qualified reviewers, necessitates innovative approaches to peer review. While large language model (LLMs) offer potential for automating this process, ...
Managing time-sensitive deliveries in settings like hospitals is a challenging task, especially when multiple pickup and delivery requests need to be coordinated efficiently within strict time windows. This paper focuses ...
Plant disease classification using machine learning in a real agricultural field environment is a difficult task. Often, an automated plant disease diagnosis method might fail to capture and interpret discriminatory ...
Dance poses represent a complex human body-part movement, and express emotions and gesture. Dance pose classification is a challenging problem in computer vision. Convolutional Neural Networks (CNNs) have witnessed significant ...