16. International Conference on Computational Pathology and Bioinformatics

The International Research Conference is a federated organization dedicated to bringing together a significant number of diverse scholarly events for presentation within the conference program. Events will run over a span of time during the conference depending on the number and length of the presentations. With its high quality, it provides an exceptional value for students, academics and industry researchers.

International Conference on Computational Pathology and Bioinformatics aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of Computational Pathology and Bioinformatics. It also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of Computational Pathology and Bioinformatics.

Prospective authors are kindly encouraged to contribute to and help shape the conference through submissions of their research abstracts, papers and e-posters. Also, high quality research contributions describing original and unpublished results of conceptual, constructive, empirical, experimental, or theoretical work in all areas of Computational Pathology and Bioinformatics are cordially invited for presentation at the conference. The conference solicits contributions of abstracts, papers and e-posters that address themes and topics of the conference, including figures, tables and references of novel research materials.

Please ensure your submission meets the conference’s strict guidelines for accepting scholarly papers. Downloadable versions of the check list for Full-Text Papers and Abstract Papers.

Please refer to the Paper Submission Guideline, Abstract Submission Guideline and Author Information before submitting your paper.

All submitted conference papers will be blind peer reviewed by three competent reviewers. The peer-reviewed conference proceedings are indexed in the Open Science Index, Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, and other index databases. Impact Factor Indicators.

The Conference offers the opportunity to become a conference sponsor or exhibitor. To participate as a sponsor or exhibitor, please download and complete the Conference Sponsorship Request Form.

• Paper Submission
• Author Registration
• Listener Registration
• Sponsorship and Exhibition
• Volunteerism

1. Fine-Grained Sentiment Analysis: Recent Progress
   Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan
2. Identification of Vessel Class with LSTM using Kinematic Features in Maritime Traffic Control
   Davide Fuscà, Kanan Rahimli, Roberto Leuzzi
3. Anomaly Detection in a Data Center with a Reconstruction Method Using a Multi-Autoencoders Model
   Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin
4. Military Use of Artificial Intelligence under International Humanitarian Law: Insights from Canada
   Mahshid Talebian Kiakalayeh
5. Deep Learning Based 6D Pose Estimation for Bin-Picking Using 3D Point Clouds
   Hesheng Wang, Haoyu Wang, Chungang Zhuang
6. Comparative Analysis of Machine Learning Tools: A Review
   S. Sarumathi, M. Vaishnavi, S. Geetha, P. Ranjetha
7. Improved Rare Species Identification Using Focal Loss Based Deep Learning Models
   Chad Goldsworthy, B. Rajeswari Matam
8. Facial Emotion Recognition with Convolutional Neural Network Based Architecture
   Koray U. Erbas
9. A Convolutional Deep Neural Network Approach for Skin Cancer Detection Using Skin Lesion Images
   Firas Gerges, Frank Y. Shih
10. Reference Architecture for Intelligent Enterprise Solutions
    Shankar Kambhampaty, Harish Rohan Kambhampaty
11. Early Depression Detection for Young Adults with a Psychiatric and AI Interdisciplinary Multimodal Framework
    Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin
12. A Comparison of YOLO Family for Apple Detection and Counting in Orchards
    Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long
13. Bayesian Deep Learning Algorithms for Classifying COVID-19 Images
    I. Oloyede
14. Model of Optimal Centroids Approach for Multivariate Data Classification
    Pham Van Nha, Le Cam Binh

Adaptive Few-Shot Deep Metric Learning
Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian