AIMC Topic: Neural Networks, Computer

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Self-supervised learning with a contrastive VideoMoCo framework for Saudi Arabic sign language recognition using 3D convolutional networks.

Scientific reports
Saudi Arabic Sign Language (SArSL) recognition poses significant challenges due to its complex spatio-temporal structure and the scarcity of annotated datasets. This paper introduces a self-supervised learning framework built upon the Video Momentum ...

An AI-powered smart Agribot for detecting locusts in farmlands using IoT and deep learning.

Scientific reports
In many countries, locusts have significantly harmed agricultural production. To prevent their spread, the Agriculture Robot (Agribot) with cutting-edge technologies like the Internet of Things (IoT) and Machine Learning (ML) can be a possible soluti...

Multi-stage knowledge distillation with layer fusion-based deep learning approach for skin cancer classification.

Scientific reports
Skin cancer is one of the most common types of cancer globally, caused by prolonged exposure to the sun's UV rays. Despite recent developments in research, early diagnosis, prevention, and treatment, skin cancer remains a significant health concern. ...

AIP-Net: an attention-integrated pyramid network for computer-aided diagnosis and segmentation of gastric lesion in ultrasound images.

Physics in medicine and biology
Automatic segmentation of gastric lesions in ultrasound images is crucial for the early diagnosis and treatment of gastric cancer, the second leading cause of cancer-related deaths worldwide. However, the limited amount of related research and the ch...

A high-resolution network with adaptive spatial channel fusion for retinal vessel segmentation.

Biomedical physics & engineering express
Accurate segmentation of retinal vessels is critical for the diagnosis of ophthalmic diseases. However, this task is made challenging by two issues: vast-scale variations from major arteries to fine capillaries often lead to a fractured vessel topolo...

OneProt: Towards multi-modal protein foundation models via latent space alignment of sequence, structure, binding sites and text encoders.

PLoS computational biology
Recent advances in Artificial Intelligence have enabled multi-modal systems to model and translate diverse information spaces. Extending beyond text and vision, we introduce OneProt, a multi-modal Deep Learning model for proteins that integrates stru...

Comparing machine learning, deep learning, and reinforcement learning performance in Culex pipiens predictive modeling.

PloS one
Several machine learning (ML) and deep learning (DL) methods have been used to predict the presence of species in classification problems. Another set of methods, called reinforcement learning (RL), has been used in training agents to perform various...

DSSA-TCN: Exploiting adaptive sparse attention and diffusion graph convolutions in temporal convolutional networks for traffic flow forecasting.

PloS one
Accurate traffic flow forecasting is essential for intelligent transportation systems, yet the nonlinear and dynamically evolving spatio-temporal dependencies in urban road networks make reliable prediction challenging. Existing graph-based and atten...

CattleNet-XAI: An explainable CNN framework for efficient cattle weight estimation.

PloS one
Accurate estimation of cattle weight is essential for effective farm management, health assessment, and productivity optimization. Traditional manual methods for weight estimation, however, are labor-intensive, time-consuming, and prone to inaccuraci...

A comparative study of MLP and LSTM neural networks for shale gas production prediction based on numerical simulation data.

PloS one
Accurate prediction of shale gas production is essential for optimizing reservoir development and improving production efficiency. In this study, a numerical simulation model was first developed to systematically calculate daily shale gas production ...