Barrett's lesion detection using a minimal integer-based neural network for embedded systems integration

Embedded processing architectures are often integrated into devices to develop novel functions in a cost-effective medical system. In order to integrate neural networks in medical equipment, these models require specialized optimizations for preparing their integration in a high-efficiency and power-constrained environment. In this paper, we research the feasibility of quantized networks with limited memory for the detection of Barrett’s neoplasia. An Efficientnet-lite1+Deeplabv3 architecture is proposed, which is trained using a quantization-aware training scheme, in order to achieve an 8-bit integer-based model. The performance of the quantized model is comparable with float32 precision models. We show that the quantized model with only 5-MB memory is capable of reaching the same performance scores with 95% Area Under the Curve (AUC), compared to a fullprecision U-Net architecture, which is 10× larger. We have also optimized the segmentation head for efficiency and reduced the output to a resolution of 32×32 pixels. The results show that this resolution captures sufficient segmentation detail to reach a DICE score of 66.51%, which is comparable to the full floating-point model. The proposed lightweight approach also makes the model quite energy-efficient, since it can be real-time executed on a 2-Watt Coral Edge TPU. The obtained low power consumption of the lightweight Barrett’s esophagus neoplasia detection and segmentation system enables the direct integration into standard endoscopic equipment

Markets drive the specialization strategies of forest peoples

Engagement in the market changes the opportunities and strategies of forest-related peoples. Efforts to support rural development need to better understand the potential importance of markets and the way people respond to them. To this end, we compared 61 case studies of the commercial production and trade of nontimber forest products from Asia, Africa, and Latin America. The results show that product use is shaped by local markets and institutions, resource abundance, and the relative level of development. Larger regional patterns are also important. High-value products tend to be managed intensively by specialized producers and yield substantially higher incomes than those generated by the less specialized producers of less managed, low-value products. We conclude that commercial trade drives a process of intensified production and household specialization among forest peoples. Copyright © 2004 by the author(s)

Prioritize smallholder cultivation of oil palm in Indonesia, urges researcher Tania Li

This PDF was modified slightly for accessibility. To view the original version, please visit the following link: https://news.globallandscapesforum.org/27297/interview-prioritize-smallholder-cultivation-of-oil-palm-in-indonesia-urges-researcher-tania-li