Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks by A.V. Dobshik, S.K. Verbitskiy, I.A. Pestunov, K.M. Sherman, Yu.N. Sinyavskiy, A.A. Tulupov, V.B. Berikov

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Encoder–Decoder Variant Analysis for Semantic Segmentation of Gastrointestinal Tract Using UW-Madison Dataset by Neha Sharma, Sheifali Gupta, Dalia H. Elkamchouchi, Salil Bharany

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A new method for early diagnosis and treatment of meniscus injury of knee joint in student physical fitness tests based on deep learning method by Yan Fang, Lu Liu, Qingyu Yang, Shuang Hao, Zhihai Luo

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Results of monitoring on the spawning run of autumn chum salmon at the observation point in Tyr in 2023 by I. A. Vaizova, A. I. Nikiforov, V. Y. Kolobov, V. V. Kharitonov

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Deep Models for Stroke Segmentation: Do Complex Architectures Always Perform Better? by Ahmed Soliman, Yalda Zafari-Ghadim, Yousif Yousif, Ahmed Ibrahim, Amr Mohamed, Essam A. Rashed, Mohamed A. Mabrok

“…The accurate segmentation of stroke lesions is crucial for the diagnosis and treatment of stroke patients, as it provides spatial information about affected brain regions and the extent of damage. …”
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ONLINE NEWS STORIES ON THE 2022 PRESIDENTIAL CANDIDATES by Yolanda L. Pasia

“…News being factual and trustworthy is one of the most reliable information. Facts must be interpreted carefully to influence or inform readers rightly and not be victimized by false information. …”
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UAV-Based Multi-Sensor Data Fusion for 3D Building Detection by Mohsen Shahraki, Ahmed El-Rabbany, Ahmed Elamin

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STUDY ON DEEP LEARNING MODELS FOR THE CLASSIFICATION OF VR SICKNESS LEVELS by Haechan NA, Yoon Sang KIM

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Cost Effectiveness of Livestock Guardian Dogs for Predator Control by Tina L. Saitone, Ellen M. Bruno

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Research Review of Deep Learning in Colon Polyp Image Segmentation by LI Guowei, LIU Jing, CAO Hui, JIANG Liang

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Multilabel Classification of Radiology Image Concepts Using Deep Learning by Vito Santamato, Agostino Marengo

“…This dataset consists of radiology images with multiple CUIs associated with each image and is organized into seven categories based on their modality information. In this study, transfer learning techniques were applied, with the models initially pre-trained on the ImageNet dataset and subsequently fine-tuned on the ImageCLEF dataset. …”
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Enhancing Railway Earthquake Early Warning Systems with a Low Computational Cost STA/LTA-Based S-Wave Detection Method by Satoshi Katakami, Naoyasu Iwata

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Multiple sclerosis diagnosis with brain MRI retrieval: A deep learning approach by R.M. Haggag, Eman M. Ali, M.E. Khalifa, Mohamed Taha

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Spoof speech classification using deep speaker embeddings and machine learning models by Mohammed Hamzah Alsalihi, Dávid Sztahó

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Evaluation of Hydrogeological Conditions, in the three Al-Mishraq Sulphur fields, northern Iraq by Mohammed Abdilfattah Ali, Sabbar Abdullah Salih, Amera Ismail Hussain

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Developing transferable and universal IR biomarkers for intraoperative colorectal cancer diagnosis via FTIR spectroscopy by Ran Li, Heather C. Allen

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SGM-EMA: Speech Enhancement Method Score-Based Diffusion Model and EMA Mechanism by Yuezhou Wu, Zhiri Li, Hua Huang

“…The model leverages the symmetric structure of U-Net to extract speech features and captures contextual information and local details across different scales using the EMA mechanism, improving speech quality in noisy environments. …”
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Urban Public Space Safety Perception and the Influence of the Built Environment from a Female Perspective: Combining Street View Data and Deep Learning by Shudi Chen, Sainan Lin, Yao Yao, Xingang Zhou

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Pear Fruit Detection Model in Natural Environment Based on Lightweight Transformer Architecture by Zheng Huang, Xiuhua Zhang, Hongsen Wang, Huajie Wei, Yi Zhang, Guihong Zhou

“…First, based on the original model, the backbone was replaced with a lightweight FasterNet network. Secondly, HiLo, an improved and efficient attention mechanism with high and low-frequency information extraction, was used to make the model lightweight and improve the feature extraction ability of Xinli No. 7 in complex environments. …”
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SUNet: Coffee Leaf Disease Detection Using Hybrid Deep Learning Model by Deepak Thakur, Tanya Gera, Ambika Aggarwal, Madhushi Verma, Manjit Kaur, Dilbag Singh, Mohammed Amoon

“…A pyramid pooling module captures multi-scale contextual information. The model is tested using two benchmark datasets, JMuBEN and JMuBEN2. …”
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