%20aims%20to%20extend%20deep%20models%20from%20static%20and%20enclosed%20environments%20to%20dynamic%20and%20complex%20scenarios%2C%20enabling%20systems%20to%20continuously%20acquire%20new%20knowledge%20of%20novel%20categories%20without%20forgetting%20previously%20learned%20knowledge.%20Recent%20CL%20models%20have%20gradually%20shifted%20towards%20the%20utilization%20of%20pre-trained%20models%20(PTMs)%20with%20parameter-efficient%20fine-tuning%20(PEFT)%20strategies.%20However%2C%20continual%20fine-tuning%20still%20presents%20a%20serious%20challenge%20of%20catastrophic%20forgetting%20due%20to%20the%20absence%20of%20previous%20task%20data.%20Additionally%2C%20the%20fine-tune-then-frozen%20mechanism%20suffers%20from%20performance%20limitations%20due%20to%20feature%20channels%20suppression%20and%20insufficient%20training%20data%20in%20the%20first%20CL%20task.%20To%20this%20end%2C%20this%20paper%20proposes%20feature%20transformation%20tuning%20(FeTT)%20model%20to%20non-parametrically%20fine-tune%20backbone%20features%20across%20all%20tasks%2C%20which%20not%20only%20operates%20independently%20of%20CL%20training%20data%20but%20also%20smooths%20feature%20channels%20to%20prevent%20excessive%20suppression.%20Then%2C%20the%20extended%20ensemble%20strategy%20incorporating%20different%20PTMs%20with%20FeTT%20model%20facilitates%20further%20performance%20improvement.%20We%20further%20elaborate%20on%20the%20discussions%20of%20the%20fine-tune-then-frozen%20paradigm%20and%20the%20FeTT%20model%20from%20the%20perspectives%20of%20discrepancy%20in%20class%20marginal%20distributions%20and%20feature%20channels.%20Extensive%20experiments%20on%20CL%20benchmarks%20validate%20the%20effectiveness%20of%20our%20proposed%20method.)
Advance knowledge with our remarkable scientific frontiers | interactive and incremental learning of spatial object collection of numerous research images. accurately representing education, school, and academic. perfect for research publications and studies. Each frontiers | interactive and incremental learning of spatial object image is carefully selected for superior visual impact and professional quality. Suitable for various applications including web design, social media, personal projects, and digital content creation All frontiers | interactive and incremental learning of spatial object images are available in high resolution with professional-grade quality, optimized for both digital and print applications, and include comprehensive metadata for easy organization and usage. Discover the perfect frontiers | interactive and incremental learning of spatial object images to enhance your visual communication needs. Comprehensive tagging systems facilitate quick discovery of relevant frontiers | interactive and incremental learning of spatial object content. Reliable customer support ensures smooth experience throughout the frontiers | interactive and incremental learning of spatial object selection process. Our frontiers | interactive and incremental learning of spatial object database continuously expands with fresh, relevant content from skilled photographers. Regular updates keep the frontiers | interactive and incremental learning of spatial object collection current with contemporary trends and styles. Time-saving browsing features help users locate ideal frontiers | interactive and incremental learning of spatial object images quickly.