尾叶桉无性系多性状遗传分析

对广西山口林场、钦廉林场天堂分场及钦州市犀牛脚镇等3个地点20个以尾叶桉为主参试无性系6、12、18、42个月生的生长性状进行分析与遗传测定.结果表明:参试的20个无性系生长性状在无性系、地点和无性系×地点交互效应上均存在极显著差异;42个月生参试的20个无性系在不同试验地点平均生长量表现为:钦廉林场天堂分场>山口林场>钦州市犀牛脚镇,性状综合分析及评定表明12、15、18号等3个尾叶桉无性系适应性广,具速生丰产性,可推广利用;3个试点选择12、15、18号3个普适型无性系时,其单株材积遗传增益可达35.32%-47.57%.     

Visual Schemas in Neural Networks for Object Recognition and Scene Analysis

VISOR is a large connectionist system that shows how visual schemas can be learned, represented and used through mechanisms natural to neural networks. Processing in VISOR is based on cooperation, competition, and parallel bottom-up and top-down activation of schema representations. VISOR is robust against noise and variations in the inputs and parameters. It can indicate the confidence of its analysis, pay attention to important minor differences, and use context to recognize ambiguous objects. Experiments also suggest that the representation and learning are stable, and behavior is consistent with human processes such as priming, perceptual reversal and circular reaction in learning. The schema mechanisms of VISOR can serve as a starting point for building robust high-level vision systems, and perhaps for schema-based motor control and natural language processing systems as well.