![]() ![]() Please refer the csv file to select the best accuracy of the previous task's model. # : the directory path which the previous task's model are stored in. 3 # : the directory path which you want to store the new model. # add_new_task_script.sh # : which GPU you want to use. Please cite following paper if these codes help your research: Our integrated multitask model can achieve similar accuracy with only 39.9% of the original size. The proposed packing-and-expanding method is effective and easy to implement, which can iteratively shrink and enlarge the model to integrate new functions. Unlike previous methods growing monotonically in size, our approach maintains the compactness in continual learning. ![]() To effectively integrate them, a continual learning approach to learn new tasks without forgetting is introduced. Simultaneously running multiple modules is a key requirement for a smart multimedia system for facial applications including face recognition, facial expression understanding, and gender identification. The code is released for academic research use only. ![]() Wan, Chein-Hung Chen, Yi-Ming Chan, Chu-Song Chen Official implementation of Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning ( Poster)Ĭreated by Steven C. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |