Male infertility contributes substantially to the global infertility burden, and sperm analysis remains central to diagnosis, treatment planning, and assisted reproductive technology. Conventional semen evaluation, however, is labor-intensive, operator-dependent, and limited by inter- and intra-observer variability, motivating the development of objective and reproducible computational approaches.
arXiv:2606. 20438v1 Announce Type: new Abstract: Male infertility is a major cause of couple infertility, often linked to abnormal sperm morphology.
By Zahra Asghari Varzaneh, Reza Khoshkangini, Thomas Ebner, Lars Johansson
The paper introduces Cross-Scale Channel-wise Knowledge Distillation (CSCWD), a training-time framework that transfers high‑resolution spatial representations from a YOLO11m‑P2 teacher to a lightweight YOLO11n student without changing the student’s inference architecture. CSCWD aligns teacher P2 features with student P3 while also applying same‑scale distillation at deeper pyramid levels, yielding a 2.92‑point mAP@0.5 improvement over the baseline and a 2.09‑point gain over same‑scale distillation alone. In zero‑shot tests on DUT‑Anti‑UAV and on a Raspberry Pi 5, the 2.58‑million‑parameter student reaches 50.32% mAP@0.5 at 82.32 ms latency (12.15 fps) with negligible runtime or memory increase.
By Amir Zamani, Zeinab Ghasemi-Naraghi
arXiv:2606. 25463v1 Announce Type: cross Abstract: This study introduces Blasto-Net, a multi-task deep learning model for comprehensive blastocyst analysis.
By Zahra Asghari Varzaneh, Reza Khoshkangini, Magnus Johnsson, Thomas Ebner, Lars Johansson
arXiv:2609.23061v1 Announce Type: new
Abstract: Small-object detection in UAV imagery is challenged by weak visual evidence, ambiguous boundaries, dense object distributions, and complex backgrounds....
By Linduo Wei, Junjie Fan, Yijun Mai, Yong Qi
arXiv:2607. 08429v1 Announce Type: cross Abstract: Male infertility is a significant yet often underdiagnosed aspect of reproductive health, with semen analysis serving as the cornerstone of clinical evaluation.
By Shahnawaz Qureshi, Raja Khurram Shahzad, Muhammad Fozan, Emal Kawal, Syed Aziz Shah, Sattam Al-Anazi, Syed MuhammadZeeshan Iqbal
This paper provides a detailed overview of the Ultralytics YOLO family from YOLOv5 to YOLO27, highlighting key architectural changes, benchmarking results, and deployment considerations. It discusses the evolution of each version—YOLO27’s scale‑adaptive dual architecture, YOLO26’s loss and optimization refinements, YOLO11’s efficiency focus, YOLOv8’s anchor‑free detection, and YOLOv5’s modular ecosystem—alongside performance metrics on COCO and latency on TensorRT. The review also surveys applications in robotics, agriculture, surveillance, and manufacturing, and outlines future challenges such as dense scene handling, CNN‑Transformer integration, and hardware‑aware optimization.
By Ranjan Sapkota, Manoj Karkee
arXiv:2609.13647v1 Announce Type: new
Abstract: The rapid development of unmanned aerial vehicle (UAV) technology has made aerial-image object detection increasingly important for natural-resource mo...
By Hao Wang
arXiv:2608. 20144v1 Announce Type: new Abstract: Women's health remains substantially under-resourced in medical imaging research, with pelvic pathologies such as polycystic ovary syndrome (PCOS) and pelvic fracture both suffering from a scarcity of public, well-annotated benchmark data despite their clinical importance.
By Siam Tahsin Bhuiyan, Rashedur Rahman, Sefatul Wasi, Halima Khatun, Ashraful Islam, AKM Mahbubur Rahman, Saadia Binte Alam, M Ashraful Amin
The paper introduces CARNIVAL, a model for protein annotation in cryo-electron tomography (cryo-ET) volumes that leverages simulated data and a forward model to generate domain‑specific augmented paired views for self‑supervised training. By incorporating simulation‑derived protein positions and identities into the architecture and loss function, the model localises semantic information at protein locations. CARNIVAL is evaluated on real tomograms without finetuning and outperforms a state‑of‑the‑art contrastive model that lacks forward‑model paired views or privileged information.
By Bogdan Toader, Kiarash Jamali, Tanmay A. M. Bharat, Sjors H. W. Scheres
arXiv:2607. 00385v1 Announce Type: cross Abstract: Automated malaria diagnosis from blood smear microscopy is a critical challenge in global health AI; in resource-limited settings, the scarcity of expert microscopists remains the primary bottleneck to timely and accurate diagnosis.
By Kaysarul Anas Apurba, Md Hasibul Hasan, Mohammed Ali, Tanzilur Rahman
arXiv:2508. 07345v2 Announce Type: replace-cross Abstract: \textbf{Introduction:} Accurate prediction of Phage Virion Proteins (PVP) is essential for genomic studies due to their crucial role as structural elements in bacteriophages.
By Samiha Afaf Neha, Md. Ishrak Khan, Abir Ahammed Bhuiyan