会议信息

ICIPCN 2027: International Conference on Image Processing and Capsule Networks

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截稿日期:
2026-10-29 还有 18 天
通知日期:
2026-11-26
会议日期:
2027-01-21
会议地点:
Tamil Nadu, India
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ICIPCN
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会伴指数 (CP-I)

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全站第 3,482 名 / 共 5,695 个会议 · 前 62%

计算机视觉与模式识别 第 177 / 246

证据有限：这个会议不在 CCF / ICORE / QUALIS 任何一份榜单里，也没有录用率数据，因此分数的大部分回落到了中性基准。
学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%) 无数据 —— 按中性基准 50 分计入 —
社区关注 (10%)
8
资料公开度 (15%)
35

用到的输入: 过去 24 个月打开过本页的研究者：2 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 25% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-11

征稿

ICIPCN 2027 (International Conference on Image Processing and Capsule Networks) is an academic conference held in Tamil Nadu, India on 2027-01-21. The paper submission deadline is 2026-10-29. Acceptance notifications are sent on 2026-11-26.

Scope To advance the frontiers of image processing, 7th International Conference on Image Processing and Capsule Networks [ICIPCN 2027] is dedicated to providing a comprehensive platform for the exploration of the latest breakthroughs in computational intelligence, with advanced models such as Capsule Networks [CapsNets]. Scheduled as a three-day conference program on 21–23, January 2027, this extended conference aims to explore and discuss about the cutting-edge research and applications, unveiling a new era of image processing. This conference will extensively cover the architecture, functioning, and applications of image processing technologies. Attendees will explore how the advanced image processing concepts enhance the representation and understanding of complex visual data. We invite discussions on innovative image and video recognition facilitated by Capsule and Neural Networks, showcasing superior capabilities and paving the way for advancements in various fields. Image Processing Image Recognition and Analysis Image Segmentation and Edge Detection Image Texture Analysis Medical Imaging Systems Image Acquisition, Reconstruction and Synthesis Feature Extraction Techniques Image Reconstructions and Losses Medical Interpretability and Explainable Deep Learning Frameworks Image Processing for Multispectral Images Image Enhancement and Restoration Pattern Recognition and Capsule Networks in Object Tracking Face and Gesture Recognition Techniques Capsule Networks Capsules in Image Analysis Deep Learning in Image Analysis Pattern Recognition and Machine Learning Big Data Analytics and Imaging Visual Content Analysis Capsule Based Biometric Technologies Cognitive Vision of Image Processing Capsules in Adaptive Image Processing Machine Learning in Capsule Neural Networks Capsule Implementation in Image Systems Capsules and Digital Image Processing Techniques Routing Mechanisms in Capsule Networks
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