Intelligent segmentation and staging system for esophageal cancer based on DAEUnet and ConvNeXt networks by XIONG Lingyan, WANG Runyuan, ZHANG Fanghong, ZHANG Fanghong

Get full text

An overview of limnological studies in Brazilian fish farms by Brenda Sthefanie Teixeira, Diego Guimarães Florêncio Pujoni, Cristiane Freitas de Azevedo Barros

“…Nevertheless, there is still a lack of information and studies on this topic to support informed decision-making. …”
Get full text

Bite First, Bleed Later: How Philippine <i>Trimeresurus</i> Pit Viper Venoms Hijack Blood Clotting by Daniel Albert E. Castillo, Lorenzo Seneci, Abhinandan Chowdhury, Marilyn G. Rimando, Bryan G. Fry

“…Consistent with pseudo-procoagulant/thrombin-like activity, the resulting fibrin clots were weak and transient, thereby contributing to net anticoagulation through the depletion of fibrinogen levels. …”
Get full text

3D Model Classification Based on Contrastive Learning by QU Zhongshui, LIU Shan, GAO Yuan, DING Bo

“…The experimental results show that the classification accuracy of the 3D model respectively reaches 99. 4% and 97. 5% on the ModelNet10 and ModelNet40 datasets.…”
Get full text

CL-SR: Boosting Imbalanced Image Classification with Contrastive Learning and Synthetic Minority Oversampling Technique Based on Rough Set Theory Integration by Xiaoling Gao, Nursuriati Jamil, Muhammad Izzad Ramli

Get full text

A algorithm for low light image enhancement in coal mine underground based on illumination constraints by Yuchen BAI, Zuohua MIAO, Houyou XU, Mengting WANG

“…Experiments were conducted in four different scenarios, comparing this algorithm against TBEFN, RUAS, MBLLEN, KinD, and Retinex-Net algorithms. Results indicate that this algorithm surpasses others in visual information fidelity (VIF), structural similarity index metric (SSIM), and peak signal to noise ratio (PSNR), achieving averages of 0.58, 0.61, and 16.58 respectively. …”
Get full text

Short‐term electric power and energy balance optimization scheduling based on low‐carbon bilateral demand response mechanism from multiple perspectives by Juan Li, Yonggang Li, Huazhi Liu

“…Comprehensive case studies from three different perspectives verify that this method can effectively realize the low‐carbon economic operation of the system, with the peak net load reduced by 24.02% and valley net load increased by 20.43%. …”
Get full text

Detecting early gastrointestinal polyps in histology and endoscopy images using deep learning by Intissar Dhrari Hajsalem, Yassine Ben Ayed

Get full text

Medium-Term Minimum Demand Forecasting Based on the Parallel LSTM-MLP Model by Dosung Kim, Deukyoung Lee, Sung-Kwan Joo, Young-Min Wi

“…Recent trends indicate a decline in demand coupled with extensive solar power utilization during the spring season, resulting in increased behind-the-meter (BTM) PV generation, subsequently reducing the net demand. This reduction introduces stability issues in the power grid. …”
Get full text

The diagnostic value of MRI segmentation technique for shoulder joint injuries based on deep learning by Lina Dai, Md Gapar Md Johar, Mohammed Hazim Alkawaz

Get full text

An Efficient 3D Model Retrieval Method Based on Convolutional Neural Network by Bo Ding, Lei Tang, Yong-jun He

“…Experiments on the rigid 3D model datasets ModelNet10 and ModelNet40 and the nonrigid 3D model dataset McGill10 show that the proposed method has achieved retrieval accuracy rates of 94%, 92%, and 100%, respectively.…”
Get full text

Machine learning-based spatio-temporal assessment of land use/land cover change in Barishal district of Bangladesh between 1988 and 2024 by Walida Zaman, H Rainak Khan Real

“…An analysis of multi-temporal LULC maps reveals a net increase in wetland (0.35 %), built-up (1.81 %), vegetation (8.48 %), and a net decrease in agriculture (−10.33 %) and bare soil (−0.36 %), primarily due to indiscriminate land use transitions. …”
Get full text

Uncovering the Diagnostic Power of Radiomic Feature Significance in Automated Lung Cancer Detection: An Integrative Analysis of Texture, Shape, and Intensity Contributions by Sotiris Raptis, Christos Ilioudis, Kiki Theodorou

Get full text

Use of Explainable Artificial Intelligence for Analyzing and Explaining Intrusion Detection Systems by Pamela Hermosilla, Mauricio Díaz, Sebastián Berríos, Héctor Allende-Cid

“…By applying these methods to the XGBoost and TabNet models trained on the UNSW-NB15 dataset, the results indicated distinct global feature importance rankings between the model types and revealed greater consistency of local explanations for the tree-based XGBoost model compared to the deep learning-based TabNet. …”
Get full text

Research on Key Technologies of Image Steganography Based on Simultaneous Deception of Vision and Deep Learning Models by Fan Zhang, Yanhua Dong, Hongyu Sun

“…Experimental results validate the effectiveness of the VRIS model, achieving high PSNR and SSIM scores on the LFW dataset and demonstrating significant deception capabilities against the ResNet50 model on the Mini-ImageNet dataset, with an impressive misclassification rate of 99.24%.…”
Get full text

Quantum behaved Intelligent Variant of Gravitational Search Algorithm with Deep Neural Networks for Human Activity Recognition by Sonika Jindal, Monika Sachdeva, Alok K. S. Kushwaha

“…Here, the DNN models of ResNet-50V2 and ResNet-101V2 are included for the classification of activities. …”
Get full text

Facilitating real-time LED-based photoacoustic imaging with DenP2P: An optimized conditional generative adversarial deep learning solution by Avijit Paul, Srivalleesha Mallidi

“…Photoacoustic imaging (PAI) benefits from the optical absorption contrast of the tissue while achieving greater depth information with ultrasound resolution than the other optical imaging platforms. …”
Get full text

YOLO-RDM: A high accuracy and efficient algorithm for magnetic tile surface defect detection with practical applications. by Wei Niu, Cheng Lv, Enxu Zhang, Zhongbin Wei

“…Finally, we replace the original backbone network of YOLOv8 with the MogaNet network. MogaNet is a module that aggregates contextual information, enhancing the network's discriminative power, learning efficiency, and ability to capture defect features in images. …”
Get full text

Employing the concept of stacking ensemble learning to generate deep dream images using multiple CNN variants by Lafta Alkhazraji, Ayad R. Abbas, Abeer S. Jamil, Zahraa Saddi Kadhim, Wissam Alkhazraji, Sabah Abdulazeez Jebur, Bassam Noori Shaker, Mohammed Abdallazez Mohammed, Mohanad A. Mohammed, Basim Mohammed Al-Araji, Abdulkareem Z. Mohmmed, Wasiq Khan, Bilal Khan, Abir Jaafar Hussain

Get full text

Hierarchical Swin Transformer Ensemble with Explainable AI for Robust and Decentralized Breast Cancer Diagnosis by Md. Redwan Ahmed, Hamdadur Rahman, Zishad Hossain Limon, Md Ismail Hossain Siddiqui, Mahbub Alam Khan, Al Shahriar Uddin Khondakar Pranta, Rezaul Haque, S M Masfequier Rahman Swapno, Young-Im Cho, Mohamed S. Abdallah

Get full text