Self-supervision advances morphological profiling by unlocking powerful image representations by Vladislav Kim, Nikolaos Adaloglou, Marc Osterland, Flavio M. Morelli, Marah Halawa, Tim König, David Gnutt, Paula A. Marin Zapata

“…However, traditional feature extraction tools such as CellProfiler are computationally intensive and require frequent parameter adjustments. …”
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Image processing method based on aerospace monitoring by A. I. Mitsiukhin, I. I. Pikirenya

“…Such characteristics of binary objects as a spatial boundary and a contour were used as deciphering signs. These features make it possible to describe the shape of an object, its geometric parameters and search for images with specific spatial structures. …”
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Lightweight deep learning model with ResNet14 and spatial attention for anterior cruciate ligament diagnosis by Herman Herman, Yogan Jaya Kumar, Sek Yong Wee, Vinod Kumar Perhakaran

“…In this study, we contribute to the development of an automated diagnostic model for anterior cruciate ligament (ACL) tears using a lightweight deep learning model, specifically ResNet-14, combined with a Spatial Attention mechanism to enhance diagnostic performance while conserving computational resources. The model processes knee MRI scans using a ResNet architecture, comprising a series of residual blocks and a spatial attention mechanism, to focus on the essential features in the imaging data. …”
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A numerical study of the relevance of the electrode-tissue contact area in the application of soft coagulation by Christoph Busch, Stefan J. Rupitsch, Knut Moeller

“…Consequently, it is essential to consider the contact area in computational simulations and the development of novel control features for safer and more reliable electrocoagulation.…”
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Advancing Skin Disease Diagnosis: A Multimodal Approach Utilizing Telegram Api Token Chatbot for Text and Image Analysis in Skin Disease Classification by Modigari Narendra, T. S. Harshini, L. Jani Anbarasi

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BSMD-YOLOv8: Enhancing YOLOv8 for Book Signature Marks Detection by Long Guo, Lubin Wang, Qiang Yu, Xiaolan Xie

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An Overview on RAM Memories in QCA Technology by Javad Chaharlang, Mohammad Mosleh

“…Nowadays, this technology is a good alternative for CMOS technology due to features such as high speed, low occupied area and low power consumption. …”
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Improved maximum growth rate prediction from microbial genomes by integrating phylogenetic information by Liang Xu, Emily Zakem, JL Weissman

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Positron emission tomography imaging biomarker and artificial intelligence for the characterization of solitary pulmonary nodule by Ashish Kumar Jha, Ashish Kumar Jha, Umeshkumar Baburao Sherkhane, Umeshkumar Baburao Sherkhane, Nilendu C. Purandare, Nilendu C. Purandare, Leonard Wee, Andre Dekker, Venkatesh Rangarajan, Venkatesh Rangarajan

“…BackgroundThe characterization of solitary pulmonary nodules (SPNs) as malignant or benign remains a diagnostic challenge using conventional imaging parameters. The literature suggests using combined Positron Emission Tomography (PET) and Computed Tomography (CT) to characterise a SPN. …”
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Fitting and comparison of calcium-calmodulin kinetic schemes to a common data set using non-linear mixed effects modelling. by Domas Linkevicius, Angus Chadwick, Guido C Faas, Melanie I Stefan, David C Sterratt

“…Calmodulin is a calcium binding protein that is essential in calcium signalling in the brain. There are many computational models of calcium-calmodulin binding that capture various calmodulin features. …”
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DermViT: Diagnosis-Guided Vision Transformer for Robust and Efficient Skin Lesion Classification by Xuejun Zhang, Yehui Liu, Ganxin Ouyang, Wenkang Chen, Aobo Xu, Takeshi Hara, Xiangrong Zhou, Dongbo Wu

“…Dermoscopic Feature Gate (DFG), which simulates the observation–verification operation of doctors through a convolutional gating mechanism and effectively suppresses semantic leakage of artifact regions. …”
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Rotten strawberry classification based on EfficientNet V2 algorithm fused with GCN and CA-Transformer by WANG Wei, YANG Shizhong, GONG Yucheng, GAO Sheng, DENG Zhaopeng

“…Finally, learning parameters were introduced on the basis of the traditional residual structure to achieve dynamic feature fusion.ResultsThe GC-EfficientNet V2 model improved the accuracy by 1.86% and the recall by 1.49% compared to the baseline model. …”
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Adaptive Noise-Powered Diffusion Model for Efficient and Accurate Object Detection by Xingyu Zou, Kaixu Han, Xinle Zhang, Wenhao Wang, Ning Wu

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Optimizing Monkeypox Lesions Detection With a Lightweight Hybrid Model by Mehdhar S. A. M. Al-Gaashani, Reem Ibrahim Alkanhel, Dina S. M. Hassan, Abduljabbar S. Ba Mahel, Ahmed Aziz, Mashael M. Khayyat, Ammar Muthanna

“…Grad-CAM, saliency maps, and other visualization techniques help improve clinical trust by highlighting relevant regions in input images, emphasizing key features of the lesions. The proposed model is lightweight with only 630,204 parameters, making it <inline-formula> <tex-math notation="LaTeX">$92.3\times $ </tex-math></inline-formula> smaller than ResNet152V2 (58,152,004 parameters) and <inline-formula> <tex-math notation="LaTeX">$28.7\times $ </tex-math></inline-formula> smaller than DenseNet201 (18,100,612 parameters). …”
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High-Accuracy Recognition Method for Diseased Chicken Feces Based on Image and Text Information Fusion by Duanli Yang, Zishang Tian, Jianzhong Xi, Hui Chen, Erdong Sun, Lianzeng Wang

“…Experiments demonstrate that MMCD significantly outperforms single-modal baselines in Accuracy (+8.69%), Recall (+8.72%), Precision (+8.67%), and F1 score (+8.72%). It surpasses simple feature concatenation by 2.51–2.82% and reduces parameters by 7.5M and computations by 1.62 GFLOPs versus the base ResNet50. …”
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Adaptive multilevel attention deeplabv3+ with heuristic based frame work for semantic segmentation of aerial images using improved golden jackal optimization algorithm by Anilkumar P, Venugopal P, Satheesh Kumar S, Jagannadha Naidu K

“…Multi-level attention unit has been included in the Atrous spatial pyramid pooling module in the encoder section of deeplabv3+ to bridge the semantic feature gap among encoders output. To put more weights on relevant features squeeze and excitation units has been included in the decoder section of deeplabv3+. …”
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Fast Decomposition Algorithm Based on Two-Dimensional Wavelet Transform for Image Processing of Graphic Design by Feifei Jiang, Wenting Yao

“…In this paper, we propose a fast decomposition algorithm image processing method based on a new transform of the wavelet transform, which mainly addresses the problems of large computation of feature points and long-time consumption of traditional image processing algorithms. …”
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YOLOv5 garbage classification method with GhostNet by Li Yao, Hu Junguo, Le Yang

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Image Classification Model Based on Contrastive Learning With Dynamic Adaptive Loss by Quandeng Gou, Jingxuan Zhou, Zi Li, Fangrui Zhang, Yuheng Ren

“…Notably, the model achieves high classification accuracy while maintaining a relatively low parameter size (23.9MB) and computational complexity (5.7Mflops). …”
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Using Wearable Sensors for Sex Classification and Age Estimation from Walking Patterns by Rizvan Jawad Ruhan, Tahsin Wahid, Ashikur Rahman, Abderrahmane Leshob, Raqeebir Rab

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