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MetaV: A Pioneer in feature Augmented Meta-Learning Based Vision Transformer for Medical Image Classification
Image classification, a fundamental task in computer vision, faces challenges concerning limited data handling, interpretability, improved feature...
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ASI-DBNet: An Adaptive Sparse Interactive ResNet-Vision Transformer Dual-Branch Network for the Grading of Brain Cancer Histopathological Images
Brain cancer is the deadliest cancer that occurs in the brain and central nervous system, and rapid and precise grading is essential to reduce...
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Novel artificial intelligent transformer U-NET for better identification and management of prostate cancer
Advancements in artificial intelligence (AI) strengthens life-altering technology that can not only reduce human workload but also enhance speed and...
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A Novel Deep Learning Model for Medical Image Segmentation with Convolutional Neural Network and Transformer
Accurate segmentation of medical images is essential for clinical decision-making, and deep learning techniques have shown remarkable results in this...
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EG-TransUNet: a transformer-based U-Net with enhanced and guided models for biomedical image segmentation
Although various methods based on convolutional neural networks have improved the performance of biomedical image segmentation to meet the precision...
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Computer Vision for Plant Disease Recognition: A Comprehensive Review
Agriculture has undergone a remarkable transformation, transitioning from traditional methods that were used for centuries to technology-driven...
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Computer Vision-Based Smart Monitoring and Control System for Crop
The agricultural sector is rapidly undergoing digital transformation, leveraging advanced technologies like artificial intelligence (AI) to...
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GraphsformerCPI: Graph Transformer for Compound–Protein Interaction Prediction
Accurately predicting compound–protein interactions (CPI) is a critical task in computer-aided drug design. In recent years, the exponential growth...
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Advancements in deep learning for accurate classification of grape leaves and diagnosis of grape diseases
Plant diseases cause significant agricultural losses, demanding accurate detection methods. Traditional approaches relying on expert knowledge may be...
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Multi-class Cancer Classification of Whole Slide Images Through Transformer and Multiple Instance Learning
Whole slide images (WSIs) are high-resolution and lack localized annotations, whose classification can be treated as a multiple instance learning...
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LiteTrans: Reconstruct Transformer with Convolution for Medical Image Segmentation
The combination of convolution and Transformer applied to medical image segmentation has achieved great success. However, it still cannot reach...
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P-TransUNet: an improved parallel network for medical image segmentation
Deep learning-based medical image segmentation has made great progress over the past decades. Scholars have proposed many novel transformer-based...
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T-KD: two-tier knowledge distillation for a lightweight underwater fish species classification model
The classification of underwater fish species holds significant importance for fisheries management. Nevertheless, existing deep fish classification...
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TEC-miTarget: enhancing microRNA target prediction based on deep learning of ribonucleic acid sequences
BackgroundMicroRNAs play a critical role in regulating gene expression by binding to specific target sites within gene transcripts, making the...
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scGPT: toward building a foundation model for single-cell multi-omics using generative AI
Generative pretrained models have achieved remarkable success in various domains such as language and computer vision. Specifically, the combination...
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Real-time fire detection algorithms running on small embedded devices based on MobileNetV3 and YOLOv4
AimFires are a serious threat to people’s lives and property. Detecting fires quickly and effectively and extinguishing them in the nascent stage is...
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iU-Net: a hybrid structured network with a novel feature fusion approach for medical image segmentation
In recent years, convolutional neural networks (CNNs) have made great achievements in the field of medical image segmentation, especially full...
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Field cabbage detection and positioning system based on improved YOLOv8n
BackgroundPesticide efficacy directly affects crop yield and quality, making targeted spraying a more environmentally friendly and effective method...
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LTPConstraint: a transfer learning based end-to-end method for RNA secondary structure prediction
BackgroundRNA secondary structure is very important for deciphering cell’s activity and disease occurrence. The first method which was used by the...
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PrCRS: a prediction model of severe CRS in CAR-T therapy based on transfer learning
BackgroundCAR-T cell therapy represents a novel approach for the treatment of hematologic malignancies and solid tumors. However, its implementation...
