TY  - GEN
N2  - This volume constitutes reviewed and selected papers from the 11th International Advanced Computing Conference, IACC 2021, held in December 2021. The 47 full papers and 4 short papers presented in the volume were thorougly reviewed and selected from 246 submissions. The papers are organized in the following topical sections: application of artificial intelligence and machine learning in healthcare; application of AI for emotion and behaviour prediction; problem solving using reinforcement learning and analysis of data; advance uses of RNN and regression techniques; special intervention of AI.
DO  - 10.1007/978-3-030-95502-1
DO  - doi
AB  - This volume constitutes reviewed and selected papers from the 11th International Advanced Computing Conference, IACC 2021, held in December 2021. The 47 full papers and 4 short papers presented in the volume were thorougly reviewed and selected from 246 submissions. The papers are organized in the following topical sections: application of artificial intelligence and machine learning in healthcare; application of AI for emotion and behaviour prediction; problem solving using reinforcement learning and analysis of data; advance uses of RNN and regression techniques; special intervention of AI.
T1  - Advanced computing :11th international advanced computing conference, IACC 2021, Msida, Malta, December 18-19, 2021, revised selected papers /
DA  - 2022.
CY  - Cham, Switzerland :
AU  - Garg, Deepak,
AU  - Jagannathan, Sarangapani,
AU  - Gupta, Ankur,
AU  - Garg, Lalit,
AU  - Gupta, Suneet,
VL  - 1528
CN  - QA75.5
PB  - Springer,
PP  - Cham, Switzerland :
PY  - 2022.
N1  - Includes author index.
ID  - 1444324
KW  - Computer science
KW  - Informatique
SN  - 9783030955021
SN  - 3030955028
TI  - Advanced computing :11th international advanced computing conference, IACC 2021, Msida, Malta, December 18-19, 2021, revised selected papers /
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-95502-1
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-95502-1
ER  -