Add EMSE Paper: Challenges and practices of deep learning model reeng…

…ineering: A case study on computer vision

bibs/journal/2024-emse-wenxin.bib

@@ -0,0 +1,15 @@
+
+@article{jiang_challenges_2024,
+	title = {Challenges and practices of deep learning model reengineering: A case study on computer vision},
+	volume = {29},
+	issn = {1573-7616},
+	url = {https://doi.org/10.1007/s10664-024-10521-0},
+	doi = {10.1007/s10664-024-10521-0},
+	abstract = {Many engineering organizations are reimplementing and extending deep neural networks from the research community. We describe this process as deep learning model reengineering. Deep learning model reengineering — reusing, replicating, adapting, and enhancing state-of-the-art deep learning approaches — is challenging for reasons including under-documented reference models, changing requirements, and the cost of implementation and testing.},
+	pages = {142},
+	number = {6},
+	journaltitle = {Empirical Software Engineering},
+	shortjournal = {Empirical Software Engineering},
+	author = {Jiang, Wenxin and Banna, Vishnu and Vivek, Naveen and Goel, Abhinav and Synovic, Nicholas and Thiruvathukal, George K. and Davis, James C.},
+	date = {2024-08-20},
+}